Learn More
Conformational sampling is one of the bottlenecks in fragment-based protein structure prediction approaches. They generally start with a coarse-grained optimization where mainchain atoms and centroids of side chains are considered, followed by a fine-grained optimization with an all-atom representation of proteins. It is during this coarse-grained phase(More)
MOTIVATION Clustering is commonly used to identify the best decoy among many generated in protein structure prediction when using energy alone is insufficient. Calculation of the pairwise distance matrix for a large decoy set is computationally expensive. Typically, only a reduced set of decoys using energy filtering is subjected to clustering analysis. A(More)
In protein folding, clustering is commonly used as one way to identify the best decoy produced. Initializing the pairwise distance matrix for a large decoy set is computationally expensive. We have proposed a fast method that works even on large decoy sets. This method is implemented in a software called Durandal. Durandal has been shown to be consistently(More)
Many biological processes are performed by a group of proteins rather than by individual proteins. Proteins involved in the same biological process often form a densely connected sub-graph in a protein-protein interaction network. Therefore, finding a dense sub-graph provides useful information to predict the function or protein complex of uncharacterised(More)
Ab initio phasing is one of the remaining challenges in protein crystallography. Recent progress in computational structure prediction has enabled the generation of de novo models with high enough accuracy to solve the phase problem ab initio. This `ab initio phasing with de novo models' method first generates a huge number of de novo models and then(More)
Recent advancements in computational methods for protein-structure prediction have made it possible to generate the high-quality de novo models required for ab initio phasing of crystallographic diffraction data using molecular replacement. Despite those encouraging achievements in ab initio phasing using de novo models, its success is limited only to those(More)
De novo structure prediction can be defined as a search in conformational space under the guidance of an energy function. The most successful de novo structure prediction methods, such as Rosetta, assemble the fragments from known structures to reduce the search space. Therefore, the fragment quality is an important factor in structure prediction. In our(More)